AgentSkillsCN

agentuity-cli-cloud-vector-upsert

在向量存储中添加或更新向量。需要身份验证。适用于 Agentuity 云平台运维。

SKILL.md
--- frontmatter
name: agentuity-cli-cloud-vector-upsert
description: Add or update vectors in the vector storage. Requires authentication. Use for Agentuity cloud platform operations
version: "0.1.24"
license: Apache-2.0
allowed-tools: "Bash(agentuity:*)"
argument-hint: "<namespace> [key]"
metadata:
  command: "agentuity cloud vector upsert"
  tags: "mutating updates-resource slow requires-auth uses-stdin"

Cloud Vector Upsert

Add or update vectors in the vector storage

Prerequisites

  • Authenticated with agentuity auth login

Usage

bash
agentuity cloud vector upsert <namespace> [key] [options]

Arguments

ArgumentTypeRequiredDescription
<namespace>stringYes-
<key>stringNo-

Options

OptionTypeRequiredDefaultDescription
--documentstringYes-document text to embed
--embeddingsstringYes-pre-computed embeddings as JSON array
--metadatastringYes-metadata as JSON object
--filestringYes-path to JSON file containing vectors, or "-" for stdin

Examples

Upsert a single vector with document text:

bash
bunx @agentuity/cli vector upsert products doc1 --document "Comfortable office chair"

Upsert with metadata:

bash
bunx @agentuity/cli vector upsert products doc1 --document "Chair" --metadata '{"category":"furniture"}'

Upsert with pre-computed embeddings:

bash
bunx @agentuity/cli vector upsert embeddings vec1 --embeddings "[0.1, 0.2, 0.3]"

Bulk upsert from JSON file:

bash
bunx @agentuity/cli vector upsert products --file vectors.json

Bulk upsert from stdin:

bash
cat vectors.json | bunx @agentuity/cli vector upsert products -

Output

Returns JSON object:

json
{
  "success": "boolean",
  "namespace": "string",
  "count": "number",
  "results": "array",
  "durationMs": "number"
}
FieldTypeDescription
successbooleanWhether the operation succeeded
namespacestringNamespace name
countnumberNumber of vectors upserted
resultsarrayUpsert results with key-to-id mappings
durationMsnumberOperation duration in milliseconds